Note: The job is a remote job and is open to candidates in USA. CSC Generation is the AI-native holding company re-engineering omnichannel retail. As a Staff Data Scientist, you will design and ship production pricing systems that influence margin and revenue decisions across a portfolio of brands. Your role involves building ML systems for pricing and demand forecasting, framing business problems into ML tasks, and collaborating with cross-functional teams.
Responsibilities
- Design and build production ML systems for pricing, demand forecasting, and related revenue problems
- Frame ambiguous business problems as well-defined ML tasks with clear success criteria and measurable outcomes
- Set the standard for model evaluation, validation, and monitoring — including knowing when CV metrics are misleading and when holdout testing is the only honest answer
- Build robust predictive models across classification, regression, time series, and causal inference
- Identify and prevent data leakage, overfitting, and other failure modes before they reach production
- Design and analyze experiments to measure causal impact of pricing decisions
- Debug models that fail in production — understand why they fail, not just that they do
- Translate model limitations, uncertainty, and risk clearly to both technical and non-technical stakeholders
- Partner with product, engineering, and business teams to ensure ML solutions solve real problems
Skills
- 7+ years of applied ML / data science experience with a track record of production systems that delivered measurable business impact
- Deep experience in pricing, demand forecasting, or revenue optimization — you have built these models end-to-end, not just consumed them
- Expert-level Python and SQL
- Deep understanding of ML fundamentals beyond API-level usage, including model evaluation, validation, and failure mode diagnosis
- Strong grounding in causal inference and experimental design, including the ability to distinguish correlation from causal result
- Ability to work with messy, real-world data and make pragmatic tradeoffs under ambiguity
- Familiarity with cloud ML platforms (GCP/Vertex AI or AWS/SageMaker)
- MS or PhD in Statistics, Computer Science, Operations Research, or a related quantitative field
- Experience in e-commerce, retail, marketplace, or pricing-intensive industries such as airlines, ride-sharing, or fintech
Benefits
- Comprehensive benefits including paid time off, RRSP match, group benefits, and employee discounts across portfolio brands.
- Comprehensive benefits including paid time off, 401(k) match, medical, dental, vision, supplemental coverage, and employee discounts across portfolio brands.
Company Overview
Company H1B Sponsorship